{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"two_layer_net.ipynb","provenance":[],"collapsed_sections":[]},"language_info":{"name":"python"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fBr6lFivMTen","executionInfo":{"status":"ok","timestamp":1618990714992,"user_tz":-480,"elapsed":19847,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"98e9c1cb-f896-404c-c9e9-2a77a9816b8e"},"source":["# This mounts your Google Drive to the Colab VM.\n","from google.colab import drive\n","drive.mount('/content/drive', force_remount=True)\n","\n","# Enter the foldername in your Drive where you have saved the unzipped\n","# assignment folder, e.g. 'cs231n/assignments/assignment1/'\n","FOLDERNAME = 'cs231n/assignments/assignment1/'\n","assert FOLDERNAME is not None, \"[!] Enter the foldername.\"\n","\n","# Now that we've mounted your Drive, this ensures that\n","# the Python interpreter of the Colab VM can load\n","# python files from within it.\n","import sys\n","sys.path.append('/content/drive/My Drive/{}'.format(FOLDERNAME))\n","\n","# This downloads the CIFAR-10 dataset to your Drive\n","# if it doesn't already exist.\n","%cd drive/My\\ Drive/$FOLDERNAME/cs231n/datasets/\n","!bash get_datasets.sh\n","%cd /content/drive/My\\ Drive/$FOLDERNAME"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Mounted at /content/drive\n","/content/drive/My Drive/cs231n/assignments/assignment1/cs231n/datasets\n","/content/drive/My Drive/cs231n/assignments/assignment1\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"tags":["pdf-ignore"],"id":"VpVXMdOBMTet"},"source":["# Fully-Connected Neural Nets\n","In this exercise we will implement fully-connected networks using a modular approach. For each layer we will implement a `forward` and a `backward` function. The `forward` function will receive inputs, weights, and other parameters and will return both an output and a `cache` object storing data needed for the backward pass, like this:\n","\n","```python\n","def layer_forward(x, w):\n","  \"\"\" Receive inputs x and weights w \"\"\"\n","  # Do some computations ...\n","  z = # ... some intermediate value\n","  # Do some more computations ...\n","  out = # the output\n","   \n","  cache = (x, w, z, out) # Values we need to compute gradients\n","   \n","  return out, cache\n","```\n","\n","The backward pass will receive upstream derivatives and the `cache` object, and will return gradients with respect to the inputs and weights, like this:\n","\n","```python\n","def layer_backward(dout, cache):\n","  \"\"\"\n","  Receive dout (derivative of loss with respect to outputs) and cache,\n","  and compute derivative with respect to inputs.\n","  \"\"\"\n","  # Unpack cache values\n","  x, w, z, out = cache\n","  \n","  # Use values in cache to compute derivatives\n","  dx = # Derivative of loss with respect to x\n","  dw = # Derivative of loss with respect to w\n","  \n","  return dx, dw\n","```\n","\n","After implementing a bunch of layers this way, we will be able to easily combine them to build classifiers with different architectures.\n","  "]},{"cell_type":"code","metadata":{"tags":["pdf-ignore"],"id":"S4RHC2wCMTeu","executionInfo":{"status":"ok","timestamp":1618990722416,"user_tz":-480,"elapsed":3539,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}}},"source":["# As usual, a bit of setup\n","from __future__ import print_function\n","import time\n","import numpy as np\n","import matplotlib.pyplot as plt\n","from cs231n.classifiers.fc_net import *\n","from cs231n.data_utils import get_CIFAR10_data\n","from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array\n","from cs231n.solver import Solver\n","\n","%matplotlib inline\n","plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n","plt.rcParams['image.interpolation'] = 'nearest'\n","plt.rcParams['image.cmap'] = 'gray'\n","\n","# for auto-reloading external modules\n","# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n","%load_ext autoreload\n","%autoreload 2\n","\n","def rel_error(x, y):\n","  \"\"\" returns relative error \"\"\"\n","  return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"tags":["pdf-ignore"],"colab":{"base_uri":"https://localhost:8080/"},"id":"0q7cFWJ3MTeu","executionInfo":{"status":"ok","timestamp":1618990733610,"user_tz":-480,"elapsed":9357,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"90b0073a-5d15-4f51-9b2f-da65d42806de"},"source":["# Load the (preprocessed) CIFAR10 data.\n","\n","data = get_CIFAR10_data()\n","for k, v in list(data.items()):\n","  print(('%s: ' % k, v.shape))"],"execution_count":4,"outputs":[{"output_type":"stream","text":["('X_train: ', (49000, 3, 32, 32))\n","('y_train: ', (49000,))\n","('X_val: ', (1000, 3, 32, 32))\n","('y_val: ', (1000,))\n","('X_test: ', (1000, 3, 32, 32))\n","('y_test: ', (1000,))\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"SiXPqZ7pMTeu"},"source":["# Affine layer: forward\n","Open the file `cs231n/layers.py` and implement the `affine_forward` function.\n","\n","Once you are done you can test your implementaion by running the following:"]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GED8dU1eMTeu","executionInfo":{"status":"ok","timestamp":1618990736241,"user_tz":-480,"elapsed":1003,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"86be3ff6-af69-4d4b-98b5-74b51c40a4e1"},"source":["# Test the affine_forward function\n","\n","num_inputs = 2\n","input_shape = (4, 5, 6)\n","output_dim = 3\n","\n","input_size = num_inputs * np.prod(input_shape)\n","weight_size = output_dim * np.prod(input_shape)\n","\n","x = np.linspace(-0.1, 0.5, num=input_size).reshape(num_inputs, *input_shape)\n","w = np.linspace(-0.2, 0.3, num=weight_size).reshape(np.prod(input_shape), output_dim)\n","b = np.linspace(-0.3, 0.1, num=output_dim)\n","\n","out, _ = affine_forward(x, w, b)\n","correct_out = np.array([[ 1.49834967,  1.70660132,  1.91485297],\n","                        [ 3.25553199,  3.5141327,   3.77273342]])\n","\n","# Compare your output with ours. The error should be around e-9 or less.\n","print('Testing affine_forward function:')\n","print('difference: ', rel_error(out, correct_out))"],"execution_count":5,"outputs":[{"output_type":"stream","text":["Testing affine_forward function:\n","difference:  9.769849468192957e-10\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"VEqTbeb3MTev"},"source":["# Affine layer: backward\n","Now implement the `affine_backward` function and test your implementation using numeric gradient checking."]},{"cell_type":"code","metadata":{"id":"wRxAsWuuMTev","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618990739892,"user_tz":-480,"elapsed":1044,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"1b2b94e8-9d15-49d9-f7e8-66be9e78e1f5"},"source":["# Test the affine_backward function\n","np.random.seed(231)\n","x = np.random.randn(10, 2, 3)\n","w = np.random.randn(6, 5)\n","b = np.random.randn(5)\n","dout = np.random.randn(10, 5)\n","\n","dx_num = eval_numerical_gradient_array(lambda x: affine_forward(x, w, b)[0], x, dout)\n","dw_num = eval_numerical_gradient_array(lambda w: affine_forward(x, w, b)[0], w, dout)\n","db_num = eval_numerical_gradient_array(lambda b: affine_forward(x, w, b)[0], b, dout)\n","\n","_, cache = affine_forward(x, w, b)\n","dx, dw, db = affine_backward(dout, cache)\n","\n","# The error should be around e-10 or less\n","print('Testing affine_backward function:')\n","print('dx error: ', rel_error(dx_num, dx))\n","print('dw error: ', rel_error(dw_num, dw))\n","print('db error: ', rel_error(db_num, db))"],"execution_count":6,"outputs":[{"output_type":"stream","text":["Testing affine_backward function:\n","dx error:  5.399100368651805e-11\n","dw error:  9.904211865398145e-11\n","db error:  2.4122867568119087e-11\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"NVh-NsMFMTew"},"source":["# ReLU activation: forward\n","Implement the forward pass for the ReLU activation function in the `relu_forward` function and test your implementation using the following:"]},{"cell_type":"code","metadata":{"id":"JCT4PevfMTew","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618990742841,"user_tz":-480,"elapsed":1191,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"a3169dbe-d5a5-428f-f0c2-56bb91d45098"},"source":["# Test the relu_forward function\n","\n","x = np.linspace(-0.5, 0.5, num=12).reshape(3, 4)\n","\n","out, _ = relu_forward(x)\n","correct_out = np.array([[ 0.,          0.,          0.,          0.,        ],\n","                        [ 0.,          0.,          0.04545455,  0.13636364,],\n","                        [ 0.22727273,  0.31818182,  0.40909091,  0.5,       ]])\n","\n","# Compare your output with ours. The error should be on the order of e-8\n","print('Testing relu_forward function:')\n","print('difference: ', rel_error(out, correct_out))"],"execution_count":7,"outputs":[{"output_type":"stream","text":["Testing relu_forward function:\n","difference:  4.999999798022158e-08\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"eh6hAwdqMTew"},"source":["# ReLU activation: backward\n","Now implement the backward pass for the ReLU activation function in the `relu_backward` function and test your implementation using numeric gradient checking:"]},{"cell_type":"code","metadata":{"id":"1MW01qJbMTew","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618990745114,"user_tz":-480,"elapsed":1066,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"190828ac-f34b-420c-a962-ce5c3f73273d"},"source":["np.random.seed(231)\n","x = np.random.randn(10, 10)\n","dout = np.random.randn(*x.shape)\n","\n","dx_num = eval_numerical_gradient_array(lambda x: relu_forward(x)[0], x, dout)\n","\n","_, cache = relu_forward(x)\n","dx = relu_backward(dout, cache)\n","\n","# The error should be on the order of e-12\n","print('Testing relu_backward function:')\n","print('dx error: ', rel_error(dx_num, dx))"],"execution_count":8,"outputs":[{"output_type":"stream","text":["Testing relu_backward function:\n","dx error:  3.2756349136310288e-12\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"tags":["pdf-inline"],"id":"fcvHosn7MTex"},"source":["## Inline Question 1: \n","\n","We've only asked you to implement ReLU, but there are a number of different activation functions that one could use in neural networks, each with its pros and cons. In particular, an issue commonly seen with activation functions is getting zero (or close to zero) gradient flow during backpropagation. Which of the following activation functions have this problem? If you consider these functions in the one dimensional case, what types of input would lead to this behaviour?\n","1. Sigmoid\n","2. ReLU\n","3. Leaky ReLU\n","\n","## Answer:\n","[FILL THIS IN]\n"]},{"cell_type":"markdown","metadata":{"id":"TaHi_0xJMTex"},"source":["# \"Sandwich\" layers\n","There are some common patterns of layers that are frequently used in neural nets. For example, affine layers are frequently followed by a ReLU nonlinearity. To make these common patterns easy, we define several convenience layers in the file `cs231n/layer_utils.py`.\n","\n","For now take a look at the `affine_relu_forward` and `affine_relu_backward` functions, and run the following to numerically gradient check the backward pass:"]},{"cell_type":"code","metadata":{"id":"DC8K1zxYMTex","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618990749241,"user_tz":-480,"elapsed":1143,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"91e8e623-b272-4b57-98af-5a5fc053a676"},"source":["from cs231n.layer_utils import affine_relu_forward, affine_relu_backward\n","np.random.seed(231)\n","x = np.random.randn(2, 3, 4)\n","w = np.random.randn(12, 10)\n","b = np.random.randn(10)\n","dout = np.random.randn(2, 10)\n","\n","out, cache = affine_relu_forward(x, w, b)\n","dx, dw, db = affine_relu_backward(dout, cache)\n","\n","dx_num = eval_numerical_gradient_array(lambda x: affine_relu_forward(x, w, b)[0], x, dout)\n","dw_num = eval_numerical_gradient_array(lambda w: affine_relu_forward(x, w, b)[0], w, dout)\n","db_num = eval_numerical_gradient_array(lambda b: affine_relu_forward(x, w, b)[0], b, dout)\n","\n","# Relative error should be around e-10 or less\n","print('Testing affine_relu_forward and affine_relu_backward:')\n","print('dx error: ', rel_error(dx_num, dx))\n","print('dw error: ', rel_error(dw_num, dw))\n","print('db error: ', rel_error(db_num, db))"],"execution_count":9,"outputs":[{"output_type":"stream","text":["Testing affine_relu_forward and affine_relu_backward:\n","dx error:  2.299579177309368e-11\n","dw error:  8.162011105764925e-11\n","db error:  7.826724021458994e-12\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"7NjJTp8dMTex"},"source":["# Loss layers: Softmax and SVM\n","Now implement the loss and gradient for softmax and SVM in the `softmax_loss` and `svm_loss` function in `cs231n/layers.py`. These should be similar to what you implemented in `cs231n/classifiers/softmax.py` and `cs231n/classifiers/linear_svm.py`.\n","\n","You can make sure that the implementations are correct by running the following:"]},{"cell_type":"code","metadata":{"id":"Eyc9SK4sMTey","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618990751948,"user_tz":-480,"elapsed":617,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"c45f5f0a-82ca-486c-a7e5-b7c65a67bde9"},"source":["np.random.seed(231)\n","num_classes, num_inputs = 10, 50\n","x = 0.001 * np.random.randn(num_inputs, num_classes)\n","y = np.random.randint(num_classes, size=num_inputs)\n","\n","dx_num = eval_numerical_gradient(lambda x: svm_loss(x, y)[0], x, verbose=False)\n","loss, dx = svm_loss(x, y)\n","\n","# Test svm_loss function. Loss should be around 9 and dx error should be around the order of e-9\n","print('Testing svm_loss:')\n","print('loss: ', loss)\n","print('dx error: ', rel_error(dx_num, dx))\n","\n","dx_num = eval_numerical_gradient(lambda x: softmax_loss(x, y)[0], x, verbose=False)\n","loss, dx = softmax_loss(x, y)\n","\n","# Test softmax_loss function. Loss should be close to 2.3 and dx error should be around e-8\n","print('\\nTesting softmax_loss:')\n","print('loss: ', loss)\n","print('dx error: ', rel_error(dx_num, dx))"],"execution_count":10,"outputs":[{"output_type":"stream","text":["Testing svm_loss:\n","loss:  8.999602749096233\n","dx error:  1.4021566006651672e-09\n","\n","Testing softmax_loss:\n","loss:  2.3025458445007376\n","dx error:  8.234144091578429e-09\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"8_nc-TvDMTey"},"source":["# Two-layer network\n","Open the file `cs231n/classifiers/fc_net.py` and complete the implementation of the `TwoLayerNet` class. Read through it to make sure you understand the API. You can run the cell below to test your implementation."]},{"cell_type":"code","metadata":{"id":"Fjgs31eaMTey","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618990756004,"user_tz":-480,"elapsed":1123,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"5e607aaf-df27-4211-8cb0-b08473c18b22"},"source":["np.random.seed(231)\n","N, D, H, C = 3, 5, 50, 7\n","X = np.random.randn(N, D)\n","y = np.random.randint(C, size=N)\n","\n","std = 1e-3\n","model = TwoLayerNet(input_dim=D, hidden_dim=H, num_classes=C, weight_scale=std)\n","\n","print('Testing initialization ... ')\n","W1_std = abs(model.params['W1'].std() - std)\n","b1 = model.params['b1']\n","W2_std = abs(model.params['W2'].std() - std)\n","b2 = model.params['b2']\n","assert W1_std < std / 10, 'First layer weights do not seem right'\n","assert np.all(b1 == 0), 'First layer biases do not seem right'\n","assert W2_std < std / 10, 'Second layer weights do not seem right'\n","assert np.all(b2 == 0), 'Second layer biases do not seem right'\n","\n","print('Testing test-time forward pass ... ')\n","model.params['W1'] = np.linspace(-0.7, 0.3, num=D*H).reshape(D, H)\n","model.params['b1'] = np.linspace(-0.1, 0.9, num=H)\n","model.params['W2'] = np.linspace(-0.3, 0.4, num=H*C).reshape(H, C)\n","model.params['b2'] = np.linspace(-0.9, 0.1, num=C)\n","X = np.linspace(-5.5, 4.5, num=N*D).reshape(D, N).T\n","scores = model.loss(X)\n","correct_scores = np.asarray(\n","  [[11.53165108,  12.2917344,   13.05181771,  13.81190102,  14.57198434, 15.33206765,  16.09215096],\n","   [12.05769098,  12.74614105,  13.43459113,  14.1230412,   14.81149128, 15.49994135,  16.18839143],\n","   [12.58373087,  13.20054771,  13.81736455,  14.43418138,  15.05099822, 15.66781506,  16.2846319 ]])\n","scores_diff = np.abs(scores - correct_scores).sum()\n","assert scores_diff < 1e-6, 'Problem with test-time forward pass'\n","\n","print('Testing training loss (no regularization)')\n","y = np.asarray([0, 5, 1])\n","loss, grads = model.loss(X, y)\n","correct_loss = 3.4702243556\n","assert abs(loss - correct_loss) < 1e-10, 'Problem with training-time loss'\n","\n","model.reg = 1.0\n","loss, grads = model.loss(X, y)\n","correct_loss = 26.5948426952\n","assert abs(loss - correct_loss) < 1e-10, 'Problem with regularization loss'\n","\n","# Errors should be around e-7 or less\n","for reg in [0.0, 0.7]:\n","  print('Running numeric gradient check with reg = ', reg)\n","  model.reg = reg\n","  loss, grads = model.loss(X, y)\n","\n","  for name in sorted(grads):\n","    f = lambda _: model.loss(X, y)[0]\n","    grad_num = eval_numerical_gradient(f, model.params[name], verbose=False)\n","    print('%s relative error: %.2e' % (name, rel_error(grad_num, grads[name])))"],"execution_count":11,"outputs":[{"output_type":"stream","text":["Testing initialization ... \n","Testing test-time forward pass ... \n","Testing training loss (no regularization)\n","Running numeric gradient check with reg =  0.0\n","W1 relative error: 1.83e-08\n","W2 relative error: 3.20e-10\n","b1 relative error: 9.83e-09\n","b2 relative error: 4.33e-10\n","Running numeric gradient check with reg =  0.7\n","W1 relative error: 2.53e-07\n","W2 relative error: 7.98e-08\n","b1 relative error: 1.56e-08\n","b2 relative error: 9.09e-10\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"QI-yIHNcMTez"},"source":["# Solver\n","Open the file `cs231n/solver.py` and read through it to familiarize yourself with the API. You also need to imeplement the `sgd` function in `cs231n/optim.py`. After doing so, use a `Solver` instance to train a `TwoLayerNet` that achieves about `36%` accuracy on the validation set."]},{"cell_type":"code","metadata":{"id":"LdAOkmiFMTez","colab":{"base_uri":"https://localhost:8080/"},"outputId":"37e08e92-2797-47d5-ca85-eeef27ebb635"},"source":["input_size = 32 * 32 * 3\n","hidden_size = 50\n","num_classes = 10\n","model = TwoLayerNet(input_size, hidden_size, num_classes)\n","solver = None\n","\n","##############################################################################\n","# TODO: Use a Solver instance to train a TwoLayerNet that achieves about 36% #\n","# accuracy on the validation set.                                            #\n","##############################################################################\n","# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n","\n","solver = Solver(model, data,\n","                    update_rule='sgd',\n","                    optim_config={\n","                      'learning_rate': 1e-3,\n","                    },\n","                    lr_decay=0.95,\n","                    num_epochs=10, batch_size=100,\n","                    print_every=100, verbose = True)\n","solver.train()\n","print('Validation accuracy: ', solver.best_val_acc)\n","\n","# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n","##############################################################################\n","#                             END OF YOUR CODE                               #\n","##############################################################################"],"execution_count":null,"outputs":[{"output_type":"stream","text":["(Iteration 1 / 4900) loss: 2.300089\n","(Epoch 0 / 10) train acc: 0.171000; val_acc: 0.170000\n","(Iteration 101 / 4900) loss: 1.782419\n","(Iteration 201 / 4900) loss: 1.803466\n","(Iteration 301 / 4900) loss: 1.712676\n","(Iteration 401 / 4900) loss: 1.693946\n","(Epoch 1 / 10) train acc: 0.399000; val_acc: 0.428000\n","(Iteration 501 / 4900) loss: 1.711237\n","(Iteration 601 / 4900) loss: 1.443683\n","(Iteration 701 / 4900) loss: 1.574904\n","(Iteration 801 / 4900) loss: 1.526751\n","(Iteration 901 / 4900) loss: 1.352554\n","(Epoch 2 / 10) train acc: 0.463000; val_acc: 0.443000\n","(Iteration 1001 / 4900) loss: 1.340071\n","(Iteration 1101 / 4900) loss: 1.386843\n","(Iteration 1201 / 4900) loss: 1.489919\n","(Iteration 1301 / 4900) loss: 1.353077\n","(Iteration 1401 / 4900) loss: 1.467951\n","(Epoch 3 / 10) train acc: 0.477000; val_acc: 0.430000\n","(Iteration 1501 / 4900) loss: 1.337133\n","(Iteration 1601 / 4900) loss: 1.426819\n","(Iteration 1701 / 4900) loss: 1.348675\n","(Iteration 1801 / 4900) loss: 1.412626\n","(Iteration 1901 / 4900) loss: 1.354764\n","(Epoch 4 / 10) train acc: 0.497000; val_acc: 0.467000\n","(Iteration 2001 / 4900) loss: 1.422221\n","(Iteration 2101 / 4900) loss: 1.360665\n","(Iteration 2201 / 4900) loss: 1.546539\n","(Iteration 2301 / 4900) loss: 1.196704\n","(Iteration 2401 / 4900) loss: 1.401958\n","(Epoch 5 / 10) train acc: 0.508000; val_acc: 0.483000\n","(Iteration 2501 / 4900) loss: 1.243567\n","(Iteration 2601 / 4900) loss: 1.513808\n","(Iteration 2701 / 4900) loss: 1.266416\n","(Iteration 2801 / 4900) loss: 1.485956\n","(Iteration 2901 / 4900) loss: 1.049706\n","(Epoch 6 / 10) train acc: 0.533000; val_acc: 0.492000\n","(Iteration 3001 / 4900) loss: 1.264002\n","(Iteration 3101 / 4900) loss: 1.184786\n","(Iteration 3201 / 4900) loss: 1.231162\n","(Iteration 3301 / 4900) loss: 1.353725\n","(Iteration 3401 / 4900) loss: 1.217830\n","(Epoch 7 / 10) train acc: 0.545000; val_acc: 0.489000\n","(Iteration 3501 / 4900) loss: 1.446003\n","(Iteration 3601 / 4900) loss: 1.152495\n","(Iteration 3701 / 4900) loss: 1.421970\n","(Iteration 3801 / 4900) loss: 1.222752\n","(Iteration 3901 / 4900) loss: 1.213468\n","(Epoch 8 / 10) train acc: 0.546000; val_acc: 0.474000\n","(Iteration 4001 / 4900) loss: 1.187435\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"YlF7EXswMTez"},"source":["# Debug the training\n","With the default parameters we provided above, you should get a validation accuracy of about 0.36 on the validation set. This isn't very good.\n","\n","One strategy for getting insight into what's wrong is to plot the loss function and the accuracies on the training and validation sets during optimization.\n","\n","Another strategy is to visualize the weights that were learned in the first layer of the network. In most neural networks trained on visual data, the first layer weights typically show some visible structure when visualized."]},{"cell_type":"code","metadata":{"id":"ig9Kn7q5MTez","colab":{"base_uri":"https://localhost:8080/","height":564},"executionInfo":{"status":"ok","timestamp":1618929991617,"user_tz":-480,"elapsed":2044,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"ff882497-923a-4e32-8da9-91f3b0266dba"},"source":["# Run this cell to visualize training loss and train / val accuracy\n","\n","plt.subplot(2, 1, 1)\n","plt.title('Training loss')\n","plt.plot(solver.loss_history, 'o')\n","plt.xlabel('Iteration')\n","\n","plt.subplot(2, 1, 2)\n","plt.title('Accuracy')\n","plt.plot(solver.train_acc_history, '-o', label='train')\n","plt.plot(solver.val_acc_history, '-o', label='val')\n","plt.plot([0.5] * len(solver.val_acc_history), 'k--')\n","plt.xlabel('Epoch')\n","plt.legend(loc='lower right')\n","plt.gcf().set_size_inches(15, 12)\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x864 with 2 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"code","metadata":{"id":"RAObpi7DMTez","colab":{"base_uri":"https://localhost:8080/","height":466},"executionInfo":{"status":"ok","timestamp":1618929997736,"user_tz":-480,"elapsed":3185,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"cfaa2796-5ad8-457f-a345-5c89fe015d69"},"source":["from cs231n.vis_utils import visualize_grid\n","\n","# Visualize the weights of the network\n","\n","def show_net_weights(net):\n","    W1 = net.params['W1']\n","    W1 = W1.reshape(32, 32, 3, -1).transpose(3, 0, 1, 2)\n","    plt.imshow(visualize_grid(W1, padding=3).astype('uint8'))\n","    plt.gca().axis('off')\n","    plt.show()\n","\n","show_net_weights(model)"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x576 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"cell_type":"markdown","metadata":{"id":"696LaGplMTe0"},"source":["# Tune your hyperparameters\n","\n","**What's wrong?**. Looking at the visualizations above, we see that the loss is decreasing more or less linearly, which seems to suggest that the learning rate may be too low. Moreover, there is no gap between the training and validation accuracy, suggesting that the model we used has low capacity, and that we should increase its size. On the other hand, with a very large model we would expect to see more overfitting, which would manifest itself as a very large gap between the training and validation accuracy.\n","\n","**Tuning**. Tuning the hyperparameters and developing intuition for how they affect the final performance is a large part of using Neural Networks, so we want you to get a lot of practice. Below, you should experiment with different values of the various hyperparameters, including hidden layer size, learning rate, numer of training epochs, and regularization strength. You might also consider tuning the learning rate decay, but you should be able to get good performance using the default value.\n","\n","**Approximate results**. You should be aim to achieve a classification accuracy of greater than 48% on the validation set. Our best network gets over 52% on the validation set.\n","\n","**Experiment**: You goal in this exercise is to get as good of a result on CIFAR-10 as you can (52% could serve as a reference), with a fully-connected Neural Network. Feel free implement your own techniques (e.g. PCA to reduce dimensionality, or adding dropout, or adding features to the solver, etc.)."]},{"cell_type":"code","metadata":{"scrolled":false,"id":"BFdXkVEFMTe0","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618935262792,"user_tz":-480,"elapsed":99943,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"434e57c9-5a11-4eec-9298-5333f717eaa2"},"source":["best_model = None\n","best_val_accuracy = 0.0\n","\n","#################################################################################\n","# TODO: Tune hyperparameters using the validation set. Store your best trained  #\n","# model in best_model.                                                          #\n","#                                                                               #\n","# To help debug your network, it may help to use visualizations similar to the  #\n","# ones we used above; these visualizations will have significant qualitative    #\n","# differences from the ones we saw above for the poorly tuned network.          #\n","#                                                                               #\n","# Tweaking hyperparameters by hand can be fun, but you might find it useful to  #\n","# write code to sweep through possible combinations of hyperparameters          #\n","# automatically like we did on thexs previous exercises.                          #\n","#################################################################################\n","# *****START OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n","\n","def random_choose_hyperparams(hsize_values, lr_values, epo_values, reg_values):\n","    hsize = hsize_values[np.random.randint(0,len(hsize_values))]\n","    lr = lr_values[np.random.randint(0,len(lr_values))]\n","    epo = epo_values[np.random.randint(0,len(epo_values))]\n","    reg = reg_values[np.random.randint(0,len(reg_values))]\n","    return hsize, lr, epo, reg\n","\n","input_size = 32 * 32 * 3\n","num_classes = 10\n","\n","for i in range(1):\n","    solver = None\n","    hsize, lr, epo, reg = random_choose_hyperparams([50, 80, 100],\n","                          [5e-5, 1e-4, 5e-4, 1e-3],\n","                          [10, 20], [0.05, 0.1, 0.2])\n","    model = TwoLayerNet(input_size, hsize, num_classes, reg = reg)\n","    solver = Solver(model, data,\n","                    update_rule='sgd',\n","                    optim_config={\n","                      'learning_rate': lr,\n","                    },\n","                    lr_decay=0.95,\n","                    num_epochs=epo, batch_size=100,\n","                    print_every=100, verbose = True)\n","    solver.train()\n","    print(hsize, lr, epo, reg)\n","    print('Validation accuracy: ', solver.best_val_acc)\n","    if solver.best_val_acc > best_val_accuracy:\n","        best_val_accuracy = solver.best_val_acc\n","        best_model = model\n","\n","print('Validation accuracy: ', best_val_accuracy)\n","\n","# *****END OF YOUR CODE (DO NOT DELETE/MODIFY THIS LINE)*****\n","################################################################################\n","#                              END OF YOUR CODE                                #\n","################################################################################"],"execution_count":null,"outputs":[{"output_type":"stream","text":["(Iteration 1 / 9800) loss: 2.318374\n","(Epoch 0 / 20) train acc: 0.134000; val_acc: 0.141000\n","(Iteration 101 / 9800) loss: 1.796252\n","(Iteration 201 / 9800) loss: 1.661397\n","(Iteration 301 / 9800) loss: 1.606889\n","(Iteration 401 / 9800) loss: 1.622995\n","(Epoch 1 / 20) train acc: 0.431000; val_acc: 0.461000\n","(Iteration 501 / 9800) loss: 1.483070\n","(Iteration 601 / 9800) loss: 1.738471\n","(Iteration 701 / 9800) loss: 1.271461\n","(Iteration 801 / 9800) loss: 1.349887\n","(Iteration 901 / 9800) loss: 1.622773\n","(Epoch 2 / 20) train acc: 0.480000; val_acc: 0.449000\n","(Iteration 1001 / 9800) loss: 1.503155\n","(Iteration 1101 / 9800) loss: 1.468987\n","(Iteration 1201 / 9800) loss: 1.263837\n","(Iteration 1301 / 9800) loss: 1.388845\n","(Iteration 1401 / 9800) loss: 1.452839\n","(Epoch 3 / 20) train acc: 0.532000; val_acc: 0.481000\n","(Iteration 1501 / 9800) loss: 1.547408\n","(Iteration 1601 / 9800) loss: 1.340877\n","(Iteration 1701 / 9800) loss: 1.332953\n","(Iteration 1801 / 9800) loss: 1.526423\n","(Iteration 1901 / 9800) loss: 1.237233\n","(Epoch 4 / 20) train acc: 0.532000; val_acc: 0.474000\n","(Iteration 2001 / 9800) loss: 1.373053\n","(Iteration 2101 / 9800) loss: 1.323105\n","(Iteration 2201 / 9800) loss: 1.251135\n","(Iteration 2301 / 9800) loss: 1.483254\n","(Iteration 2401 / 9800) loss: 1.271939\n","(Epoch 5 / 20) train acc: 0.579000; val_acc: 0.513000\n","(Iteration 2501 / 9800) loss: 1.221357\n","(Iteration 2601 / 9800) loss: 1.359690\n","(Iteration 2701 / 9800) loss: 1.297151\n","(Iteration 2801 / 9800) loss: 1.303413\n","(Iteration 2901 / 9800) loss: 1.344788\n","(Epoch 6 / 20) train acc: 0.563000; val_acc: 0.490000\n","(Iteration 3001 / 9800) loss: 1.168731\n","(Iteration 3101 / 9800) loss: 1.282191\n","(Iteration 3201 / 9800) loss: 1.242941\n","(Iteration 3301 / 9800) loss: 1.473912\n","(Iteration 3401 / 9800) loss: 1.321203\n","(Epoch 7 / 20) train acc: 0.598000; val_acc: 0.494000\n","(Iteration 3501 / 9800) loss: 1.228780\n","(Iteration 3601 / 9800) loss: 1.359891\n","(Iteration 3701 / 9800) loss: 1.019328\n","(Iteration 3801 / 9800) loss: 1.419004\n","(Iteration 3901 / 9800) loss: 1.069841\n","(Epoch 8 / 20) train acc: 0.582000; val_acc: 0.488000\n","(Iteration 4001 / 9800) loss: 1.247000\n","(Iteration 4101 / 9800) loss: 1.357791\n","(Iteration 4201 / 9800) loss: 1.213559\n","(Iteration 4301 / 9800) loss: 1.161534\n","(Iteration 4401 / 9800) loss: 1.107110\n","(Epoch 9 / 20) train acc: 0.612000; val_acc: 0.512000\n","(Iteration 4501 / 9800) loss: 1.128312\n","(Iteration 4601 / 9800) loss: 1.087895\n","(Iteration 4701 / 9800) loss: 1.403967\n","(Iteration 4801 / 9800) loss: 1.398084\n","(Epoch 10 / 20) train acc: 0.621000; val_acc: 0.504000\n","(Iteration 4901 / 9800) loss: 1.296222\n","(Iteration 5001 / 9800) loss: 1.251050\n","(Iteration 5101 / 9800) loss: 1.171213\n","(Iteration 5201 / 9800) loss: 1.204583\n","(Iteration 5301 / 9800) loss: 1.310433\n","(Epoch 11 / 20) train acc: 0.599000; val_acc: 0.512000\n","(Iteration 5401 / 9800) loss: 1.161847\n","(Iteration 5501 / 9800) loss: 1.169852\n","(Iteration 5601 / 9800) loss: 1.021980\n","(Iteration 5701 / 9800) loss: 1.307691\n","(Iteration 5801 / 9800) loss: 1.257751\n","(Epoch 12 / 20) train acc: 0.591000; val_acc: 0.504000\n","(Iteration 5901 / 9800) loss: 1.213289\n","(Iteration 6001 / 9800) loss: 1.164286\n","(Iteration 6101 / 9800) loss: 1.102400\n","(Iteration 6201 / 9800) loss: 1.397984\n","(Iteration 6301 / 9800) loss: 1.268312\n","(Epoch 13 / 20) train acc: 0.609000; val_acc: 0.521000\n","(Iteration 6401 / 9800) loss: 1.155814\n","(Iteration 6501 / 9800) loss: 1.117541\n","(Iteration 6601 / 9800) loss: 1.183972\n","(Iteration 6701 / 9800) loss: 1.079557\n","(Iteration 6801 / 9800) loss: 0.899054\n","(Epoch 14 / 20) train acc: 0.607000; val_acc: 0.507000\n","(Iteration 6901 / 9800) loss: 0.810508\n","(Iteration 7001 / 9800) loss: 1.016494\n","(Iteration 7101 / 9800) loss: 1.384717\n","(Iteration 7201 / 9800) loss: 1.010193\n","(Iteration 7301 / 9800) loss: 1.044378\n","(Epoch 15 / 20) train acc: 0.628000; val_acc: 0.506000\n","(Iteration 7401 / 9800) loss: 0.909823\n","(Iteration 7501 / 9800) loss: 1.256247\n","(Iteration 7601 / 9800) loss: 1.375381\n","(Iteration 7701 / 9800) loss: 1.139124\n","(Iteration 7801 / 9800) loss: 1.162603\n","(Epoch 16 / 20) train acc: 0.622000; val_acc: 0.501000\n","(Iteration 7901 / 9800) loss: 1.099523\n","(Iteration 8001 / 9800) loss: 0.964554\n","(Iteration 8101 / 9800) loss: 1.230471\n","(Iteration 8201 / 9800) loss: 1.105560\n","(Iteration 8301 / 9800) loss: 1.121105\n","(Epoch 17 / 20) train acc: 0.629000; val_acc: 0.527000\n","(Iteration 8401 / 9800) loss: 1.027470\n","(Iteration 8501 / 9800) loss: 1.061049\n","(Iteration 8601 / 9800) loss: 0.979492\n","(Iteration 8701 / 9800) loss: 1.068036\n","(Iteration 8801 / 9800) loss: 1.087340\n","(Epoch 18 / 20) train acc: 0.640000; val_acc: 0.522000\n","(Iteration 8901 / 9800) loss: 1.130142\n","(Iteration 9001 / 9800) loss: 1.236062\n","(Iteration 9101 / 9800) loss: 0.976330\n","(Iteration 9201 / 9800) loss: 0.928962\n","(Iteration 9301 / 9800) loss: 1.036988\n","(Epoch 19 / 20) train acc: 0.660000; val_acc: 0.516000\n","(Iteration 9401 / 9800) loss: 0.923907\n","(Iteration 9501 / 9800) loss: 1.011059\n","(Iteration 9601 / 9800) loss: 1.368885\n","(Iteration 9701 / 9800) loss: 0.964489\n","(Epoch 20 / 20) train acc: 0.662000; val_acc: 0.517000\n","100 0.001 20 0.1\n","Validation accuracy:  0.527\n","Validation accuracy:  0.527\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"IVOm11N7MTe0"},"source":["# Test your model!\n","Run your best model on the validation and test sets. You should achieve above 48% accuracy on the validation set and the test set."]},{"cell_type":"code","metadata":{"id":"val_accuracy","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618935268067,"user_tz":-480,"elapsed":844,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"1a9c592f-e533-4151-9046-00c60bb5e80c"},"source":["y_val_pred = np.argmax(best_model.loss(data['X_val']), axis=1)\n","print('Validation set accuracy: ', (y_val_pred == data['y_val']).mean())"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Validation set accuracy:  0.527\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"test_accuracy","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618935272811,"user_tz":-480,"elapsed":823,"user":{"displayName":"Mingyu Yang","photoUrl":"","userId":"04100620278597188865"}},"outputId":"e7fdab1e-cec9-46eb-cce9-6b58eeb32896"},"source":["y_test_pred = np.argmax(best_model.loss(data['X_test']), axis=1)\n","print('Test set accuracy: ', (y_test_pred == data['y_test']).mean())"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Test set accuracy:  0.504\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"C06AmbmCMTe0"},"source":["## Inline Question 2: \n","\n","Now that you have trained a Neural Network classifier, you may find that your testing accuracy is much lower than the training accuracy. In what ways can we decrease this gap? Select all that apply.\n","\n","1. Train on a larger dataset.\n","2. Add more hidden units.\n","3. Increase the regularization strength.\n","4. None of the above.\n","\n","$\\color{blue}{\\textit Your Answer:}$\n","\n","$\\color{blue}{\\textit Your Explanation:}$\n","\n"]},{"cell_type":"code","metadata":{"id":"C1NFDPiqMTe1"},"source":[""],"execution_count":null,"outputs":[]}]}